English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Voice authentication is drawing increasing attention and becomes anattractive alternative to passwords for mobile authentication. Recent advancesin mobile technology further accelerate the adoption of voice biometrics in anarray of diverse mobile applications. However, recent studies show that voiceauthentication is vulnerable to replay attacks, where an adversary can spoof avoice authentication system using a pre-recorded voice sample collected fromthe victim. In this paper, we propose VoiceLive, a liveness detection systemfor both text-dependent and text-independent voice authentication onsmartphones. VoiceLive detects a live user by leveraging the user's uniquevocal system and the stereo recording of smartphones. In particular, utilizingthe built-in gyroscope, loudspeaker, and microphone, VoiceLive first measuresthe smartphone's distance and angle from the user, then it captures theposition-specific time-difference-of-arrival (TDoA) changes in a sequence ofphoneme sounds to the two microphones of the phone, and uses such unique TDoAdynamic which doesn't exist under replay attacks for liveness detection.VoiceLive is practical as it doesn't require additional hardware buttwo-channel stereo recording that is supported by virtually all smartphones.Our experimental evaluation with 12 participants and different types of phonesshows that VoiceLive achieves over 99% detection accuracy at around 1% EqualError Rate (EER) on the text-dependent system and around 99% accuracy and 2%EER on the text-independent one. Results also show that VoiceLive is robust todifferent phone positions, i.e. the user is free to hold the smartphone withdistinct distances and angles.

A Continuous Liveness Detection System for Text-independent Speaker Verification